code: def test_scipy__cache_hit_miss(
      expect_cache_hit: bool,
      same_closure2: bool,
      same_variables2: bool,
      same_tf_fun_args2: bool,
      allow_unused_variables2: bool,
      compile2: bool,
  ) -> None:
      opt = gpflow.optimizers.Scipy()
  
      variables1 = _create_variables()
      counter1 = [0]
      closure1 = _loss_closure_builder(counter1, variables1)
      tf_fun_args1 = dict(experimental_relax_shapes=True)
      dummy_x = tf.concat([tf.zeros_like(var) for var in variables1], 0)
  
      if same_closure2:
          closure2 = closure1
      else:
          closure2 = _loss_closure_builder([0], variables1)
  
      if same_variables2:
          variables2 = variables1
      else:
          variables2 = [variables1[0]]  # Pick a subset of variables
  
      if same_tf_fun_args2:
          tf_fun_args2 = dict(experimental_relax_shapes=True)
      else:
          tf_fun_args2 = dict(experimental_relax_shapes=False)
  
      # Populate cache with first closure and variables
      eval_func1 = opt.eval_func(
          closure1, variables1, tf_fun_args1, True, False
      )
      eval_func1(dummy_x)
  
      # Call with passed in arguments
      eval_func2 = opt.eval_func(
          closure2,
          variables2,
          tf_fun_args2,
          compile2,
          allow_unused_variables2,
      )
      eval_func2(dummy_x)
  
      if expect_cache_hit:
          # Check that the cache was used
          assert len(opt.compile_cache) == 1
          assert _get_eval_func_closure(
              eval_func2
          ) is _get_eval_func_closure(eval_func1), "Cache hit expected"
      else:
          # Check that the cache was bypassed and a new compiled function was created, if compile=True
          if compile2:
              assert len(opt.compile_cache) == 2
          else:
              assert len(opt.compile_cache) == 1
          assert _get_eval_func_closure(
              eval_func2
          ) is not _get_eval_func_closure(
              eval_func1
          ), "Cache miss expected"
  
      # The original closure, variables and args should still be in the cache
      eval_func3 = opt.eval_func(
          closure1, variables1, tf_fun_args1, True, False
      )
      eval_func3(dummy_x)
      assert _get_eval_func_closure(
          eval_func3
      ) is _get_eval_func_closure(eval_func1), "Cache hit expected"
  
      # The closures should be run
      #   1 (during the first compilation) + 1 (if miss and closure was reused) times
      exp_count = 1 + (
          1 if not expect_cache_hit and same_closure2 else 0
      )
      assert counter1[0] == exp_count
  
imports: import unittest
  import warnings
  from typing import Any, Callable, Dict, List, Sequence, Tuple
  from unittest.mock import MagicMock
  import numpy
  import pytest
  import tensorflow
  from packaging.version import Version
  import gpflow
  from gpflow.base import AnyNDArray
  from gpflow.config import default_float
  from gpflow.models import GPR, GPModel
  from gpflow.optimizers.scipy import LossClosure
label_desc: Use image node_id 14 for calling a global function with example usage: test_scipy__cache_hit_miss(expect_cache_hit, same_closure2, same_variables2, same_tf_fun_args2, allow_unused_variables2, compile2) without return types